In the first part one of the series, we looked Flames forwards shot rates, mostly with a view to putting the top guys rates in context, both from a team and league perspective. It took me three tries and some helpful comments to ultimately get the chart right, but I blame excel for that.

The follow-up builds on that base to illustrate the effect of possession on individual shot (and goal rates) at even strength as well as gross on-ice totals and ultimately goal differential. This exercise puts some flesh on the bones of corsi/possession theory for those who wonder about the practical applications of that sort of advanced analysis.

The following table includes much of the data we had last week, but adds in some additional information to fill in some gaps.

NAME

GP

TOI/60

G

SH

TS

ES ICE

shots/game

shots/60

SF/60

SA/60

total SF

total SA

shots %

Individ SH%

DAVIDMOSS

32

11.5

2

74

76

368

2.38

12.39

30.5

26.1

187

160

53.9%

40.6%

LEESTEMPNIAK

61

12.57

12

95

107

767

1.75

8.37

27.1

27.6

346

353

49.5%

30.9%

JAROMEIGINLA

82

16.37

22

161

183

1342

2.23

8.18

23.9

29.2

535

653

45.0%

34.2%

MIKAELBACKLUND

41

13.02

2

70

72

534

1.76

8.09

28.2

25

251

222

53.0%

28.7%

OLLIJOKINEN

82

14.63

13

144

157

1200

1.91

7.85

25

31

500

620

44.6%

31.4%

MICHAELCAMMALLERI

66

13.76

17

98

115

908

1.74

7.60

26.4

28.9

400

437

47.7%

28.8%

BLAKECOMEAU

74

13.21

5

114

119

978

1.61

7.30

25.4

27.1

414

442

48.4%

28.8%

MATTSTAJAN

61

11.36

7

66

73

693

1.20

6.32

25

26.3

289

304

48.7%

25.3%

TOMKOSTOPOULOS

81

10.75

2

80

82

871

1.01

5.65

25.6

27.8

372

403

47.9%

22.1%

CURTISGLENCROSS

67

13.3

15

68

83

891

1.24

5.59

25.9

29.6

385

440

46.7%

21.6%

ALEXTANGUAY

64

13.82

10

46

56

884

0.88

3.80

23.6

29.2

348

430

44.7%

16.1%

After shots/60 (individual shots per 60/minutes of ice), SF and SA/60 shows the team's rate of shots for and against with that player. Shots % is the players ratio of shots/for at even strength. Individual shot % is the percentage of total shots that player accounted for. For example, the Flames managed 187 shots at 5on5 with David Moss on the ice last year and he personally took 76 of them for an individual SH% of (78/187) 40.6%.

Finding Expected Goals

Shots% is a subset of corsi (which involves all shots at the net including block and misses) but for simplicity we'll consider it a proxy for possession. As you can see, only Backlund and Moss we above water amongst those listed by this metric - meaning the Flames only outshot the bad guys when those two were on the ice last year in aggregate (although Comeau's NYI results are mashed into his Flames outcomes, so take his number with a grain of salt. Ditto Cammalleri and Montreal).

The Flames big guns led the team in gross shots and goals for at ES and weren't bad at personally generating shots/60. However, they were clearly on the wrong end of possession, suggesting a couple of things:

a.) with better possession, they could have spent more time in the offensive zone and therefore increased their shots on net/goal rates

b.) They gave up a lot of shots/goals against, limiting the value of their own totals

To model how an improved possession rate would affect those issues, I took the exisiting shot totals, assumed constant invidual shots % (ratio of personal shots to total shots for), a possession rate of 55% and applied league average shooting and save percentages to the results.

Here's how things shake out:

Player

Individ SH%

Shots %

total SF

delta total SF

expected TS

delta TS

expected goals

expected GF delta

total SA

delta SA

expected GA delta

expected GD delta

DAVIDMOSS

40.6%

0.55

191

4

78

2

0.2

0.3

156

-4

-0.31

0.63

MIKAELBACKLUND

28.7%

0.55

260

9

75

3

0.3

0.8

213

-9

-0.75

1.53

LEESTEMPNIAK

30.9%

0.55

384

38

119

12

1.2

3.1

315

-38

-3.05

6.18

BLAKECOMEAU

28.8%

0.55

470

57

135

16

1.7

4.6

385

-57

-4.53

9.17

JAROMEIGINLA

34.2%

0.55

653

154

223

40

4.3

12.6

535

-119

-9.49

22.08

OLLIJOKINEN

31.4%

0.55

616

116

193

36

3.8

9.5

504

-116

-9.28

18.79

MICHAELCAMMALLERI

28.8%

0.55

460

61

133

18

1.9

5.0

377

-61

-4.86

9.84

MATTSTAJAN

25.4%

0.55

326

37

83

10

1.0

3.0

267

-37

-2.97

6.02

TOMKOSTOPOULOS

22.1%

0.55

426

55

94

12

1.3

4.5

349

-55

-4.38

8.86

CURTISGLENCROSS

21.6%

0.55

453

69

98

15

1.6

5.6

371

-69

-5.50

11.13

ALEXTANGUAY

16.1%

0.55

428

80

69

13

1.4

6.6

350

-80

-6.42

12.99

The invidiual SH% and total shots while the player was on the ice last year remain constant. The shots % of 55% is a hypothetical possession rate for each guy. The total shots for is how many shots that team would have had with each player on the ice given a 55% posssesion rate. The delta SF shows the difference between this total and his actual SF total last year.

Expected TS and delta TS are similar, except they are for each player's personal shots on net totals and are arrived at by multiplying his indvidual SH% with the new total SF. "expected goals" shows the additional goals each player would have scored given a 55% possession rate and league average ES shooting percentage. "Expected GF delta" shows the additional goals the team would have scored with the player on the ice given the 55% possession rate.

The process was repeated for shots and goals against. The expected GD delta shows the difference in expected even strength goal differential between existing shots ratios and hypothetical shots ratios, assuming league average SH% and SV%.

Discussion

Lots of numbers here, but the important columns are the delta's (or "difference") which show how many more shots/goals each player could be expected given last year's shot totals and if his possession rate had been 55% (and stable, league average percentages). In the case of Jarome Iginla and Olli Jokinen, for instance, they could have personally generated 40 and 36 more shots on net respectively had they managed possession rates of 55% (rather than 45%). In terms of total shots, the team could have accrued 154 more shots with Jarome on the ice and 116 more shots with Jokinen skating last year as opposed to what they actually managed.

As a result, Jokinen and Iginla would be expected to score 4.3 and 3.8 more even strength goals each with a 10% shift in possession. In terms of total goals for when they were on the ice, the expected goal difference is 12.6 and 9.5.

In contrast, the team would have given up 119 and 116 less shots against with each guy on the ice last year, saving the club 9.49 and 9.28 goals against at 5on5. All told, not only would both guys have scored about 8 more ES goals personally, but the team would be expected to improve their goal differential by more than 22 in just Iginla's case (which is worth about 3.5 expected wins or 7 points in the standings).

The effect is obviously less pronounced for guys with less ice time. The cnage for Backlund and Moss is especially muted because both players didn't play much and were close to a 55% possession rate anyways.

Caveats

- Keep in mind an indvidual 55% possession rate is excellent-to-elite in the NHL (but certainly not impossible).

- I've assumed personal percentage of total shots on net as a constant from the season sample, but it likely varies year-to-year somewhat. That said, Iginla is usually at 30% or above, while the stingy Tanguay is usally below 20%. Moss' number is skewed by a small sample size.

- This inquiry used league average even strength personal and on-ice ES SH% and SV% to control for assumed randomness in the actual results. So that is 10.53% SH% at even strength for forwards last year, and 0.08 on-ice SH% and 0.92 on-ice SV%.

This could be done for each player using his real 2011-12 on-ice SH% and SV% however. For example, Iginla personally shot at 12% at ES last year, while his on-ice ES SH% was 10.10 and on-ice SV% was .913. That expands his expected personal goal delta to 4.9, his expected goals for delta to 15.5 and expected goal differential delta to 25.83 (!!) - or 4.31 wins/about 8.5 points in the standings. .

If people have interest in this sort of comparision, I can re-run the results and post them later.

Thanks Rex, although I don't find stats intuitive at all. Math was usually my worst subject in school and I didn't much enjoy my stats courses in University. Half the time I expect I've missed a step or done something wrong when I engage in these quantitative inquiries.

Luckily Im so interested in the results it helps push me through the research/table making part of things.

I subscribe to the Socratic idea that there are some innate mathematical traits in us as human beings, that nearly everybody can understand and comprehend mathematics to a degree. The trick is in the teaching and the method of comprehension. And enthusiasm for the end result makes anything easier to accomplish.

Math was usually my worst subject, until I had a spate of good teachers who understood how the information needed to be presented so as to best permeate my thick skull, then I was off to the races. I still hated my stats class, but at least I understood what was going on. All of that being said, the advanced analysis aspect of hockey is still enough to make my eyes glaze over.

Ya know Rex, I've suspected you were an academic for a while now. Math was never my strongest class either, but unlike you guys I avoided Stats in university all together. In the words of Chevy Chase "I was told there would be no math".

Does anyone want to speculate about whether a change in style of play may lead to more shots, or more importantly better CORSI ratings for most of the Flames players. By all accounts Bob Hartley's an uptempo, high offense type coach.

When Jonathan Willis researched Hartley's past he found he regularly deployed game choking defensive tactics. Which isn't to say he can't coach offense, just that he certainly doesn't default to an uptempo game. Like most bench bosses, he'll try to tailor his approach to the skills of team he has.